Interactive graphics with plotly

library(tidyverse)

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## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(plotly)

## 
## Attaching package: 'plotly'
## 
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
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## The following object is masked from 'package:stats':
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##     filter
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## The following object is masked from 'package:graphics':
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##     layout

3D

iris |> plot_ly(x = ~Sepal.Length, y = ~Sepal.Width, z = ~Petal.Length, color = ~Species)

## No trace type specified:
##   Based on info supplied, a 'scatter3d' trace seems appropriate.
##   Read more about this trace type -> https://plotly.com/r/reference/#scatter3d

## No scatter3d mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode

2D

iris |> plot_ly(x = ~Sepal.Length, y = ~Sepal.Width, color = ~Species)

## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plotly.com/r/reference/#scatter

## No scatter mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode

From ggplot

p <- iris |> 
  ggplot(aes(x = Sepal.Length, y = Sepal.Width, color = Species)) +
  geom_point()
p

ggplotly(p)

Hack to identify rownumber

p2 <- iris |> rownames_to_column() |> 
  ggplot(aes(x = Sepal.Length, y = Sepal.Width, color = Species, text = rowname)) +
  geom_point()
p2

ggplotly(p2)